package cn.itcast.mapreduce;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class JobMain extends Configured implements Tool {

    public int run(String[] strings) throws Exception {
        Job job = Job.getInstance(super.getConf(), JobMain.class.getSimpleName() + "-zn");

        //打包到集群上面运行时候，必须要添加以下配置，指定程序的main函数
        job.setJarByClass(JobMain.class);
        //第一步：读取输入文件解析成key，value对
        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.addInputPath(job, new
                Path("hdfs://node01:8020/wordcount"));
        //第二步：设置我们的mapper类
        job.setMapperClass(WordCountMapper.class);
        //设置我们map阶段完成之后的输出类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);
        //第三步，第四步，第五步，第六步，省略
        // 分区
//        job.setPartitionerClass(MyPartitioner.class);
        // 规约
        job.setCombinerClass(MyCombiner.class);
        // 设置reduce的个数
//        job.setNumReduceTasks(2);
        //第七步：设置我们的reduce类
        job.setReducerClass(WordCountReducer.class);
        //设置我们reduce阶段完成之后的输出类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);
        //第八步：设置输出类以及输出路径
        job.setOutputFormatClass(TextOutputFormat.class);
        TextOutputFormat.setOutputPath(job, new Path("hdfs://node01:8020/wordcount_out"));
        boolean b = job.waitForCompletion(true);

        return b ? 0 : 1;
    }

    public static void main(String[] args) throws Exception {
        Configuration entries = new Configuration();
        int run = ToolRunner.run(entries, new JobMain(), args);
        System.exit(run);
    }

}
